Proceedings Sardinia 2009, Twelfth International Waste Management and Landfill Symposium S. Margherita di Pula, Cagliari, Italy; 5 - 9 October 2009 2009 by CISA, Environmental Sanitary Engineering Centre, Italy

MODELLING TO ASSESS POLICY INSTRUMENTS

T. EKVALL*, A. BJÖRKLUND**, O. ERIKSSON°, M. LJUNGGREN SÖDERMAN*, G. ÖSTBLOM°°, M. SJÖSTRÖM°°, Å. STENMARCK* AND J.-O. SUNDQVIST*

* IVL Swedish Environmental Research Institute - P.O. Box 21060, SE-100 31 Stockholm, Sweden ** Environmental Strategies Research, Royal Institute of Technology - SE-100 44 Stockholm, Sweden ° Dept. Technology and Built Environment, Division of Building Quality, University of Gävle - SE-801 76 Gävle, Sweden °° National Institute of Economic Research - P.O. Box 3116, Kungsgatan 12-14, SE-103 62 Stockholm

SUMMARY: We refine and combine a set of existing, quantitative tools to investigate how different policy instruments affect the cost and environmental impacts of waste management in Sweden in the year 2030. The tools include the national waste statistics, a general equilibrium model of the Swedish economy, a systems engineering model of the Swedish waste-management system, and life cycle assessment. Since the system investigated is large and complex, it is important to find a good balance between accuracy and data collection efforts. Close cooperation between experts on the different tools is also essential.

1. INTRODUCTION

An on-going Swedish research programme, Towards Sustainable Waste Management (TOSUWAMA) [1], funded by the Swedish Environmental Protection Agency during 2006-2012, aims at formulating new waste policy instruments that may contribute to the development of a more sustainable waste management, shifting waste management towards the upper levels of the waste hierarchy. The research programme is interdisciplinary and involves the study of many different aspects of waste management: environmental, economic, cultural and social. Seeking the broadest scope possible, economists, ethnologists, environmental psychologists, systems analysts and futurologists carry out the research in close co-operation.

We survey existing and potential policy instruments, and formulate and assess promising alternatives. An important part of the assessment is made through refining and combining a set of existing, quantitative tools (see Figure 1): the national waste statistics (SEPA, 2008), developed in accordance with the EU regulation

on waste statistics (EU, 2002), the Environmental Medium term EConomic model (EMEC), a general equilibrium model of

the Swedish economy (Östblom and Berg, 2006),

NatWaste, a systems engineering model of the Swedish waste-management system (Ljunggren, 2000), and

life cycle assessment (LCA), which has been increasingly used for the past 20 years to take into account environmental impacts of waste management from “cradle-to-grave”.

Figure 1. Combination of tools for assessing policy instruments for sustainable waste management.

By the end of the year 2008, a list of 57 policy instruments was compiled, ranging from fiscal instruments such as taxes as subsidies, to “soft” instruments including support for various cooperative solutions (Bisaillon et al., 2008). From this list, the most interesting policy instruments are currently being extracted for further analysis with the combination of tools.

In late 2009 and 2010, the combination of tools in Figure 1 will be applied to explore how the economy, the waste management system, and the environment might be affected in the year 2030 by the different policy instruments. We use scenario analysis to deal with the large uncertainties inherent in studies of the long-term future: each policy instrument is assessed in five external scenarios with different assumptions regarding the future development of external aspects of politics, economy, technological development etc.

2. EXTERNAL SCENARIOS

The scenarios were developed as part of TOSUWAMA through an iterative process with the programme researchers. The key assumptions of affecting waste generation in the scenarios are presented in Table 1. Dreborg and Tyskeng (2008) present the scenarios regarding future waste generation in further detail.

The Reference scenario relates closely to that of the recent Long-Term Survey of the Swedish economy (Hill et al., 2008). The economy, assumingly, continues to develop as during the recent decades in the scenario ‘Global sustainability’, as well as in the Reference scenario. Climate change and sustainability policies, however, have a higher priority in the scenario ‘Global sustainability’, and the CO2 permit price is therefore assumed to be higher than in the Reference scenario. In addition, a more rapid technological change in the direction of saving primary resources reduces the waste intensities.

The scenario ‘Global markets’ is characterized by growing global markets and free trade but less concern for climate change and sustainability policies and thus the CO2 permit price is assumed to be lower than in the Reference scenario. Expanding world trade leads to higher rates of employment and economic growth in Sweden but also to higher international prices of raw materials and fossil fuels. Here also, technological change goes in the direction of saving

National waste

statistics EMEC NatWaste LCA

Waste intensities

Marginal waste

management costs

Waste quantities

Price development

Waste management

set up

Environmental

impacts

primary resources because of the increase in primary product prices and input-related waste intensities therefore decrease; however, less concern for sustainability among policy-makers as well as the public affect households’ behaviour in the direction of increased waste intensities.

Table 1. The economic key assumptions in the five external scenarios. The numbers present the annual percentage changes from the year 2006 to 2030 (Hill et al., 2008; Dreborg & Tyskeng, 2008). GDP and World trade are presented in 2006 prices. Primary product prices and Oil prices are in 2006 constant SEK.

Reference Global sustainability

Global markets

Regional markets

European sustainability

GDP 2.2 2.2 3.3 1.8 1.8 World trade 4.4 4.4 4.8 3.8 3.8 Primary product prices

0.1 0.1 1.7 1.3 0.1

Oil prices 0.8 0.8 3.0 0.8 0.8 Employment 0.2 0.2 0.5 0.2 0.3 Technological development

Moderate Rapid Rapid Slow Slow

Environmental policy-making and awareness

Moderate Strong Weak Weak Strong in the EU

The trend towards globalisation is reversed in the scenarios ‘Regional markets’ and ‘European

sustainability’, where an increased protectionism among world regions holds world trade back and thereby also slows the rate of economic growth in Sweden down. Technological change is assumed to be less rapid in these scenarios than in the other scenarios due to the weaker globalisation trend. Climate change and sustainability policies are emphasised more in the scenario ‘European sustainability’ than in the scenario ‘Regional markets’.

3. WASTE INTENSITIES

The assessments in TOSUWAMA cover, with few exceptions, the total generated waste in Sweden. Recent data on waste quantities from all sectors in the society is available from the Swedish Environmental Protection Agency who is responsible for the reporting according to the European Regulation on Waste Statistics. Waste data are available for 48 different waste types in 20 different sectors, including all economic activities in industry, business, services and households.

3.1 Current waste coefficients

The national waste statistics and data on current activities in the various sectors are used for calculating current waste intensities in each sector. For every waste type in each commercial sector we have assigned a set of waste coefficients that describes how the quantity of generated waste depends on different parameters in EMEC (Sundqvist et al., 2009): production value, consumption of energy carriers, divided into gases, motor fuels, coal, biofuels and other fuels, depreciation of capital goods,

consumption of commodities (33 different commodities are distinguished), and staff.

The EMEC model measures staff in terms of person-hours. The coefficients for staff-related

waste are then measured in terms of kg waste per person-hour. All other parameters in the list above are measured in economic terms, using the prices of the year 2006. The related waste coefficients are then given in terms of kg waste per SEK in the prices of 2006.

As far as possible and when deemed to be relevant, we have allocated the waste generation to a commodity or an energy carrier. Scrap vehicles and most of the scrap equipment are allocated to the depreciation of capital goods. Some wastes have been allocated to the staff, for example household waste from business.

The coefficients of waste from households are in EMEC given in terms of kg waste per SEK spent on different groups of consumption goods. We assigned the quantities of each waste type from households to a combination of 26 different commodities.

Waste coefficients in 2030

The waste coefficients are likely to change over time as a result of technological development and behavioural changes. These, in turn, can be affected by the economic development and by policy-making. Table 2 presents a first estimate of how the waste coefficients will develop until the year 2030 in the different external scenarios.

Table 2. First estimate of the development of waste intensities over time in the five external scenarios. The numbers present the annual percentage changes from the year 2006 to 2030 (Sundqvist et al., 2009).

Reference Global sustainability

Global markets

Regional markets

European sustainability

Firms’ input-related waste

-1 -3 -1 0 -1

Firms’ employees-related waste

0 -1 1 1 -1

Firms’ output-related waste

0 0 0 0 0

Household waste 0 -2 1.5 1 -2.5 The coefficients for input-related waste are in EMEC given in terms of kg waste per SEK

spent on specific commodities and energy carriers, or on commodities or energy carriers in general. These are likely to decline over time, because technological development can increase the yield of production processes. Such development is further stimulated in scenarios with strong environmental policies and where the real price of raw materials increase rapidly. In the scenario “Global sustainability” the input-related waste coefficients are assumed to decline by a full 3% per year, which mean the reduction will be over 50% from 2006 to 2030.

The coefficients for employee-related waste are assumed to depend mainly on the environmental awareness. For this reason, they increase in scenarios with low awareness and decrease in scenarios with a strong awareness.

The ouput-related waste coefficients are assumed to depend mainly on the technological development. This will allow for the production of more advanced products that, at least

sometimes, generate more waste in production. On the other hand, part of the technological development will also be process improvements that reduce the quantity of waste per produced item. We assume that these forces roughly balance out in the all scenarios, which means that the output-related waste coefficients of the manufacturing industry remains constant until 2030.

The waste intensities of Swedish households have been roughly constant over time, historically. The future development depends on the consumption patterns and on the environmental awareness. We assume that the waste coefficients of households will increase in scenarios with low awareness and decrease in scenarios with a strong awareness.

The estimates and assumptions regarding the future development of waste coefficients are currently being revised.

4. WASTE QUANTITIES

The resulting estimates for future waste intensities are used in EMEC, a general equilibrium model of the Swedish economy, to calculate the waste quantities in 2030. These will vary between scenarios, because the economic development and the waste intensities will both vary. They will also vary depending on the policy instruments, when these affect the economy and/or waste intensities.

The general equilibrium model EMEC includes 26 industrial sub sectors, 33 composite commodities and a public sector producing a single commodity. Produced goods and services are exported and used together with imports to create composite commodities for domestic use. Composite commodities are used as inputs by industries and for capital formation. In addition, households consume composite commodities and there are 26 consumer goods. Production demands inputs of labour, capital, energy, materials and transports. Households maximize utility subject to an income restriction, firms maximizes profit subject to resources restrictions, disposal of public services are subject to a budget constraint and the foreign sector’s import and export activities are govern by an exogenously given trade balance. The demands and supplies of commodities and resources are cleared by market prices.

The waste flows in the economy relate to production and consumption of commodities, and thus economic activity generates waste through input use in production and households’ use of outputs. Firms’ waste flows are affected by the input of materials, labour, capital and fuels, which link to their corresponding waste intensities in the model. Households’ waste flows are affected by their consumption of goods and services, which also link to corresponding waste intensities in the model. Besides production, consumption and waste intensities, the price of waste disposal services affects future waste generation in EMEC. The waste management sector, as modelled in NatWaste has the role of feeding EMEC with prices of the waste disposal services. Firms and households react on these prices, by reducing the quantities of waste generated in the economy.

The first estimates for the future waste intensities (see, e.g., Table 2) have been fed into EMEC, whose structure has been adapted to accomodate these (Sjöström & Östblom, 2009). For future waste generation to decouple from economic growth its direction must change in favour of less waste intensive products and/or the waste intensities in firms’ and households’ economic activities must decrease.

The waste bars depicted for alternative scenarios in Figures 2 and 3 are results from this test run of EMEC with waste intensities. We expect the bars to be significantly different when waste coefficients are revised (see Section 3) and as a result of iterations with NatWaste (Section 5). However, Figures 2 and 3 already reveal characteristic patterns in the generation of wastes: the impact on waste quantities of of economic growth, technological development and behavioural changes are apparent. The total non-hazardous waste increases the most in the scenario ‘Global

markets’. This scenario has high economic growth and modest assumed decreases in waste intensities. Total non-hazardous waste will increase least for the scenario ‘Global sustainability’, which has the same economic growth as the Reference scenario but much more rapid assumed decrease in waste intensities. The types of wastes affected the most by economic growth are Batteries and accumulators, Household wastes, Rubber wastes and Glass wastes, whereas Textile wastes, Wood wastes, Mineral wastes, Chemical wastes and Metal wastes are the waste types affected the most by reduced waste intensities of firms’ production and households’ consumption.

-40-20

020406080

100120140160180200220240260280300320

Batteries and accum

ulators

Household w

astes

Rubber w

astes

Glass w

astes

Discarded equipm

ent

Sorting residues

Paper w

astes

Sludges

Plastic w

astes

Mixed m

aterials

Metal w

astes

Com

bustion wastes

Mineral w

astes

Chem

ical wastes

Anim

al and vegetal wastes

Wood w

astes

Textile wastes

Total

BaselineGlobal sustainabilityGlobal marketsRegional marketsEuropean sustainability

Figure 2. Preliminary changes in percentage of Swedish non-hazardous waste quantities from 2006 to 2030 (Sjöström & Östblom, 2009). Here “Baseline” means Reference scenario.

-10

1030

5070

90

110130

150

170190

210230

250

270290

Discarded equipm

ent

Wood w

astes

Discarded vehicles

Batteries and accumulators

Contam

inated soils

Mixed m

aterials

Mineral w

astes

Spent solvents

Com

bustion wastes

Sludges

Used oils

Chem

ical wastes

Total

BaselineGlobal sustainabilityGlobal marketsRegional marketsEuropean sustainability

Figure 3. Preliminary changes in percentage of Swedish hazardous waste quantities from 2006

to 2030 (Sjöström & Östblom, 2009). Here “Baseline” means Reference scenario.

The total quantity of hazardous waste grows at a higher percentage rate than do non-hazardous waste in all scenarios. In the test run, hazardous waste grows by 159 per cent in the scenario ‘Global markets’ compared to 127 per cent for non-hazardous waste. Contrary to non-hazardous waste, the quantity of hazardous waste grows more quickly in the scenario ‘Global sustainability’ than in the scenario ‘European sustainability’. This indicates that the assumed reduction in waste intensities affects the generation of hazardous waste less than it affects the generation of non-hazardous waste.

Our preliminary results indicate that future waste generation will be closely related to economic growth, particularly for hazardous waste. To obtain a decoupling from economic growth, policy instruments will be needed to induce reductions in the waste intensities of firms and households.

5. WASTE TREATMENT

The information on the quantity of waste of different types and from different sectors and the price development over time of certain commodities from EMEC will be fed into NatWaste. NatWaste calculates the cost-effective mix of waste-treatment methods in different scenarios and with different policy instruments. As the first step in the process, the resulting marginal costs for waste treatment are fed back from NatWaste into EMEC. Then, the waste quantities are recalculated in EMEC. This iterative process will continue until a converging solution of waste quantitites and marginal costs of waste management has been found. The convergence of the iteration is granted, as the unit costs of waste treatment will not increase when the generation of waste decreases. The last step in the process is to feed the cost-effective set up of waste management from NatWaste into the LCA model for analysis of environmental impacts (see Section 6).

NatWaste is a systems engineering model for strategic planning of national waste management systems (Ljunggren, 2000). It offers the possibility to explore the co-ordination of technical waste management options by cost minimisation. Results from NatWaste specify economically optimal capacities of technical waste management options, the quantities of waste and material treated in the various options and the energy turnover.1 Technological development of specific processes until the final year of the analysis 2030 is not explicitly considered. But as a guiding principle, data representing best current commercially available technology (BAT) in a Swedish perspective is used.

The scope of NatWaste includes the so-called waste management foreground system (Figure 4). Waste of a certain quantity and composition enters the system at the point where it is collected from the waste generators (i.e., households, industries and trade). The waste is treated in the system, usually through a combination of treatment methods. Finally, from the foreground system exit (1) recovered materials to be absorbed by the markets for materials; (2) recovered compost or anaerobic digestion residues to be absorbed by the market for e.g. fertilisers; and (3) waste to be stored long-term in a landfill. Auxiliary materials (additives) are supplied for running the system. If investments in new equipment are made, capital goods are supplied to the system. Auxiliary energy in the form of electricity and fuels is supplied for running the system. Energy

1 NatWaste calculates a limited number of emissions to air and residual content of harmful substances in the waste. Presently, the substances

included are fossil carbon dioxide, methane, nitrous oxides, sulphur oxides, carbon monoxide and four heavy metals. This feature of

NatWaste is not used in this study at the advantage of LCA which offers the possibility of a broader analysis of environmental impacts.

can be recovered from the system in the form of heat, electricity and biogas, to be absorbed by the markets for energy carriers. Background systems and avoided processes are taken into account by including economic information, i.e. prices, on the material and energy flows that are transferred across the foreground system boundary. This means that the scope of the NatWaste model and the LCA model are identical, but the focus of the analysis differs: NatWaste considers the economic consequences of technical waste management options whereas the LCA model considers the environmental ones.

Figure 4. Scope of NatWaste and the LCA model developed in TOSUWAMA.

To enable the sharing of data between NatWaste and EMEC on the one hand and NatWaste and the LCA model on the other hand, much effort has been spent on harmonising waste fractions terminology, the model structure of waste treatment processes and process data. EMEC calculates waste quantities based on the aggregated waste types defined in the European Waste Statistics Directive (EWC-Stat) (EU, 2002). NatWaste and the LCA model require a higher level of detail concerning waste fractions. Thus, each waste fraction used in EMEC has been disaggregated into a number of sub-fractions so that a meaningful analysis of waste management options can be performed. Model conformity between NatWaste and the LCA model regards both the structure of the treatment processes and how these are linked to into a complete system for treating all generated waste as well as the quantitative process data.

6. ENVIRONMENTAL IMPACTS

Applying a life cycle perspective to waste-management planning and design is a means to avoid environmental suboptimization and unwanted and unforeseen indirect environmental impact.

This has been emphasized in the European Union thematic strategy on waste (EU, 2005). Our research programme applies LCA for assessing the environmental implications of

proposed waste policy instruments. For this purpose, we develop an LCA model of the national Swedish waste management system. This model includes the waste-management foreground system as well as the background system that provides electricity, fuel and additives to the waste management (see Figure 4). The model also includes processes that are avoided through output from the waste management of recovered resources, such as heat, electricity, and recycled materials. It is assumed that these recovered resources replace the production and use of a similar resource produced by some alternative means. Hence, the environmental benefit of these recovered resources is taken into account by subtracting the environmental impacts of the alternative, avoided production of these resources.

As illustrated in Figure 1, NatWaste describes the waste-management system that results from proposed policy instruments, that is the amount of each waste fraction being treated by each waste treatment method. This data is used as input to the LCA model, so that the environmental impacts of the waste management can be calculated.

All processes in the system generate emissions to the environment, and use resources derived from the environment. Collecting the environmental data has been a severe challenge because of the multitude of waste flows and treatment processes. Most of the environmental data on foreground processes has been collected from existing databases and tools, both public, commercial, and proprietary. Datasets for incineration, composting, anaerobic digestion, and landfilling have to a large extent been derived from the substance flow process models available in the Orware model. Given detailed information on the chemical composition of the waste and process data on waste treatment, Orware was applied to calculate LCI datasets for these treatment methods. To a limited extent, new inventories of process data have been collected, where representative data were not available or where data had to be updated to current conditions. Just like in NatWaste, our aim was to collect BAT data where possible, but technological development beyond BAT was not considered.

The potential environmental impacts of emissions and resource use are calculated using the CML 2 baseline method.

Linking NatWaste and the LCA model requires conformity in the selection of processes and waste fractions. It has been a challenge to ensure conformity between the models, while at the same time keeping them sufficiently flexible to allow for assessment of different types of policy instruments. This required close cooperation between model developers.

5. DISCUSSION AND CONCLUSIONS

The research programme has a quite ambitious agenda with its aim to investigate how policy instruments affect the cost and environmental impacts of waste management for nearly all solid waste flows in Sweden in the year 2030. This requires establishing: economic, technological, political and behavioural scenarios for the year 2030, the links between each waste fraction and parameters in the economy, and the economic costs and environmental impacts of various management options for each waste

fraction. An important challenge in this task is to find the appropriate level of detail. An accurate

calculation of the environmental impacts requires detailed information on the composition of the waste flows, but this easily makes the data collection unsurmountable. Despite a budget of approximately 500 kEuro and a time-frame of three years for developing the combination of tools illustrated in Figure 1, we had to make careful decisions on where waste types and

economic sectors could and must be aggregated or disaggregated. Another challenge is to link the models in such a way that information generated as output by

one tool can easily be used as input by another. This challenge became more severe because the combination of tools has to be flexible enough to be able to assess different types of policy instruments. Meeting this challenge required close cooperation between the experts and developers of the different models. This, in turn, resulted in mutual learning among the economists, systems engineers, and environmental scientists involved in the process.

We expect results from the assessment of policy instruments to be ready in the year 2010. Information on the publication of these results, and part of the environmental data, will be available at the TOSUWAMA website: www.sustainablewaste.info.

ACKNOWLEDGEMENTS

The authors thank the Swedish Environmental Protection Agency for the financial support and the researchers participating in the other projects in the research programme Towards Sustainable Waste Management.

REFERENCES

Bisaillon M, Finnveden G, Jussila Hammes J, Haraldsson M, Stenmarck Å, Sundberg J, Sundqvist J-O, Tyskeng S. (2008) Hållbar avfallshantering: Beskrivning av styrmedel. Manuscript (in Swedish).

Dreborg, K-H, Tyskeng, S., (2008) Framtida förutsättningar för en hållbar avfallshantering. TRITA-INFRA-FMS 2008:6, KTH, Stockholm.

EU (2002) Regulation (EC) No 2150/2002 of the European Parliament and the Council on Waste Statistics.

EU (2005) Taking sustainable use of resources forward - A Thematic Strategy on the prevention and recycling of waste. COM(2005) 666 final. European Commission.

Hill M, Löf P, Pettersson T. (2008) Sveriges ekonomi: Scenarier på lång sikt. SOU 2008:108. Ministry of Finance, Stockholm (in Swedish).

Ljunggren M. (2000) Modelling national waste management. Waste Management & Research 18:6, 525-537.

SCB (2001) Environmental Accounting 1993-1998. Statistical Report MI 53 SM 0101, Statistics Sweden.

SEPA (2008). Avfall i Sverige 2006. Report 5868, Swedish Environmental Protection Agency, Stockholm, Sweden. url: http://www.naturvardsverket.se/Documents/publikationer/978-91-620-5868-5.pdf (in Swedish).

Sjöström M, Östblom G. (2009) Future Waste Scenarios for Sweden on the Basis of a CGE-model, Working Paper 109, National Institute of Economic Research, Stockholm, Sweden.

Sundqvist J-O, Stenmarck Å, Ekvall T. (2009) Model for Future Waste Generation. Forthcoming, IVL Swedish Environmental Research Institute, Stockholm, Sweden.

Östblom G, Berg, C. (2006). The EMEC model: Version 2.0. Working Paper 96, National Institute of Economic Research, Stockholm, Sweden.

Author details:

Tomas Ekvall, PhD, IVL Swedish Environmental Research Institute, P.O. Box 21060, SE-100 31 Stockholm, Sweden; phone +46-(0)31-725 62 81; fax +46-(0)31-725 62 90; email tomas.ekvall@ivl.se. LicEng 1991 in energy and environmental systems analysis. PhD 1999 in technical environmental

planning with a focus on life cycle assessment and wastepaper management. Associated Professor

2004 in energy technology with a focus on energy and waste-management systems analysis.

Chairman of SETAC Europe working group on scenario development in LCA, 1999-2001. Subject editor of Journal of Cleaner Production, 1998-2005. Host of the 14th SETAC-Europe LCA Case Studies Symposium: LCA of Energy - Energy in LCA, 2007. Head of the research programme Towards Sustainable Waste Management since 2006. Anna Björklund, PhD, Assoc. Prof., Environmental Strategies Research, Royal Institute of Technology, SE-100 44 Stockholm, Sweden; email annab@infra.kth.se. Ola Eriksson, PhD, Dept. Technology and Built Environment, Division of Building Quality, University of Gävle, SE-801 76 Gävle, Sweden; email Ola.Eriksson@hig.se. Maria Ljunggren Söderman, PhD, IVL Swedish Environmental Research Institute, P.O. Box 21060, SE-100 31 Stockholm, Sweden; phone +46-(0)31-725 62 67; fax +46-(0)31-725 62 90; email maria.soderman@ivl.se. Göran Östblom, PhD, National Institute of Economic Research, P.O. Box 3116, Kungsgatan 12-14, SE-103 62 Stockholm; email goran.ostblom@konj.se. Magnus Sjöström, PhD, Ministry of Finance, Division for Tax Policy Analysis, SE-103 33 Stockholm; phone +46-(0)8-405 44 04; email magnus.sjostrom@finance.ministry.se. Åsa Stenmarck, MSc, IVL Swedish Environmental Research Institute, P.O. Box 21060, SE-100 31 Stockholm, Sweden; phone +46-(0)8-598 563 66; fax +46-(0)8-598 563 90; email asa.stenmarck@ivl.se. Jan-Olov Sundqvist, MSc, IVL Swedish Environmental Research Institute, P.O. Box 21060, SE-100 31 Stockholm, Sweden; phone +46-(0)8-598 563 74; fax +46-(0)8-598 563 90; email jan-olov.sundqvist@ivl.se.